Interface-enhanced conductivities in surfactant-mediated, solution-grown ionic crystalline complexes

IF 4.1 Q2 MATERIALS SCIENCE, MULTIDISCIPLINARY
Jihua Chen, Jong Keum, Yangyang Wang, Hanyu Wang, Bradley S. Lokitz, Guang Yang, Yue Yuan, Rajeev Kumar, R. Advíncula
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引用次数: 0

Abstract

Renewable energy is increasingly relying on optimized electrolytes and interfaces. In this work, Tween 20 and sodium chloride are selected as a model system to reveal the effects of surfactants on salt crystallization in the context of ionic conductivity and interface optimization. At a varied crystallization speed and mix ratio, it is demonstrated that the resultant solution-grown ionic crystalline complexes can achieve a highly tunable ion transport with a controllable crystalline interface. X-ray diffraction results rule out the possibility of polymorphism in the NaCl/Tween 20 systems, which further supports the importance of an optimized crystalline network for optimizing permittivity or ionic conductivity. Raman mapping and machine learning techniques are used to perform semantic segmentation on highly heterogeneous NaCl/Tween 20 complexes. Furthermore, FTIR measurements demonstrate that inter- and intra-molecular interactions play critical roles in the formation of these crystals. This work lays a foundation toward future optimization of such complex ion systems for a specific salt or crystallization modifier in energy storage or ion transport applications.
表面活性剂介导的溶液生长离子晶体复合物的界面增强电导率
可再生能源越来越依赖于优化的电解质和界面。本研究选择吐温 20 和氯化钠作为模型系统,从离子传导性和界面优化的角度揭示表面活性剂对盐结晶的影响。结果表明,在不同的结晶速度和混合比例下,溶液生长出的离子结晶复合物可以通过可控的结晶界面实现高度可调的离子传输。X 射线衍射结果排除了 NaCl/Tween 20 系统中存在多态性的可能性,这进一步证明了优化结晶网络对于优化介电常数或离子导电性的重要性。拉曼图谱和机器学习技术用于对高度异质的 NaCl/Tween 20 复合物进行语义分割。此外,傅立叶变换红外测量结果表明,分子间和分子内的相互作用在这些晶体的形成过程中发挥了关键作用。这项工作为今后优化此类复合离子系统,使其适用于能量存储或离子传输应用中的特定盐或结晶改性剂奠定了基础。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Frontiers in Nanotechnology
Frontiers in Nanotechnology Engineering-Electrical and Electronic Engineering
CiteScore
7.10
自引率
0.00%
发文量
96
审稿时长
13 weeks
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